Bibliographic record
Abstract
This thesis is an examination of the sex and gender differences in measures of relative deprivation for Winnipeg, Manitoba, and the value of these measures to predict health outcomes. Within theoretical frameworks of relative deprivation and intersectionality, principal component analysis was used to test nineteen different versions of a national area-based deprivation index using Census variables, for the total population and for males and females separately. Only one version of the deprivation index provided consistent factor scores, in keeping with the theoretical constructs, for the total, female-only and male-only populations for Winnipeg. Administrative health data were used to calculate area-level rates of select health outcomes and binomial negative regressions were then used to analyze whether the “best” index was predictive of health outcomes for the three populations. In regression models, only the “material” component of the deprivation index was predictive of the health outcomes, but results varied across the three populations. The application of the “best” deprivation index to health planning may depend on the health issue and the population in question. This thesis confirmed that examining the intersections of sex, gender and deprivation in population health research unmasks important differences that would otherwise be missed and could have implications in health planning.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".